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Russell Schwartz -

Russell Schwartz

Professor and Department Head

Russell Schwartz works in computational biology and the use of algorithms, AI, machine learning, and simulation in biomedical science.


Expertise

Topics:  Cancer Biology, Biophysics, Population Genetics, Computational Genomics, Machine Learning, Computational Biology, Artificial Intelligence, Algorithms, Phylogenetics

Industries: Research, Biotechnology

Russell Schwartz works broadly in computational biology and the use of algorithms, artificial intelligence, machine learning, and simulation in biomedical science. This has included work on problems in computational genomics, phylogenetics, population genetics, and biophysics. The largest area of his lab’s work in recent years has been cancer biology, with specific focus on clonal evolution in cancers and its role in disease progression. He is also active in bioinformatics education and improving quantitative and computational training in the biomedical field.

Media Experience

Computer science professor Sorin Istrail wins award recognizing algorithms research  — The Brown Daily Herald
Through the paper and its surrounding work, Istrail and colleagues made use of one of the pillars of computer science in genomics — recognizing that a genome can be modeled as a computational artifact and that, in doing so, one is able to access a powerful set of tools for analyzing it, according to Russell Schwartz, co-author of the paper and head of the computational biology department at Carnegie Mellon University.

Education

Ph.D., Computer Science, Massachusetts Institute of Technology

Links

Articles

A Clonal Evolution Simulator for Planning Somatic Evolution Studies —  Journal of Computational Biology

Simulating the distortion of clonal fractions in ctDNA due to spatially heterogenous selection —  Cancer Research

Reconstructing tumor clonal lineage trees incorporating single-nucleotide variants, copy number alterations and structural variations —  Bioinformatics

Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers —  Nucleic Acids Research

Semi-deconvolution of bulk and single-cell RNA-seq data with application to metastatic progression in breast cancer —  Bioinformatics

Photos